In the coming year we expect to: a. Complete optimization of our liver texture algorithms as an independent rather than liver size related image feature. This feature, in combination with the liver size measurement algorithm that we have developed will be adapted for diagnostic decision tasks. Either the pattern recognition techniques that we have developed, or, possibly, classical statistical techniques will be used for this purpose. b. If resources allow, the sensitivity, specificity, and reproducibility of the human observer's subjective diagnosis of liver images will be compared with the computer diagnoses. Receiver operating errors will be constructed by multiple observers who will be provided with images with standardized fidelity. c. If time allows, we will devise other algorithms to extract potentially useful liver image features, including liver pliability, relative liver/spleen and liver/lung uptake ratios, relative size of the right and left lobes of the liver. These image features promise to be considerably simpler to extract than the size and texture features, since the bulk of the acquisition, preprocessing, and statistical analytic work will be completed and adaptable for these purposes.